摘要
本文聚焦于智能电网中的电能质量监测与改善方法，旨在提升电力系统的稳定性和可靠性。文章首先阐述了智能电网电能质量监测的研究背景及电能质量改善方法的研究意义，并分析了国内外在该领域的研究现状。在电能质量监测技术方面，文章详细介绍了电能质量参数的实时监测方法，探讨了分布式监测系统的架构设计，并分析了大数据在电能质量监测中的创新应用，为电能质量的全面监测提供了技术支持。针对电能质量问题诊断，文章分类总结了常见的电能质量问题及其特征，提出了基于人工智能的故障诊断方法，并研究了谐波污染源定位技术，为电能质量问题的精准识别提供了有效手段。在电能质量改善策略方面，文章探讨了主动配电网中的电能质量控制方法，分析了分布式电源接入对电能质量的影响及应对策略，并研究了储能系统在电能质量改善中的实际应用，为电能质量的综合改善提供了全面指导。本研究不仅丰富了智能电网电能质量监测与改善的理论体系，也为电力系统的优化运行和可持续发展提供了重要参考。
关键词：智能电网；电能质量监测；深度学习；长短期记忆网络；多目标优化
Abstract
This article focuses on the monitoring and improvement methods of power quality in smart grids, aiming to enhance the stability and reliability of the power system. The article first elaborates on the research background of smart grid power quality monitoring and the significance of improving power quality methods, and analyzes the current research status in this field at home and abroad. In terms of power quality monitoring technology, the article provides a detailed introduction to real-time monitoring methods for power quality parameters, explores the architecture design of distributed monitoring systems, and analyzes the innovative application of big data in power quality monitoring, providing technical support for comprehensive monitoring of power quality. Regarding the diagnosis of power quality issues, this article categorizes and summarizes common power quality problems and their characteristics, proposes an artificial intelligence based fault diagnosis method, and studies harmonic pollution source localization technology, providing an effective means for accurate identification of power quality issues. In terms of power quality improvement strategies, this article explores the power quality control methods in active distribution networks, analyzes the impact of distributed power source access on power quality and response strategies, and studies the practical application of energy storage systems in power quality improvement, providing comprehensive guidance for the comprehensive improvement of power quality. This study not only enriches the theoretical system of smart grid power quality monitoring and improvement, but also provides important references for the optimized operation and sustainable development of the power system.
Keywords：Smart Grid; Power Quality Monitoring; Deep Learning; Long Short-Term Memory Network; Multi-ob jective Optimization
目 录
摘要 I
Abstract II
一、绪论 1
（一）智能电网电能质量监测的研究背景 1
（二）电能质量改善方法的研究意义 1
（三）国内外研究现状分析 2
二、智能电网电能质量监测技术 3
（一）电能质量参数实时监测方法 3
（二）分布式监测系统架构设计 3
（三）大数据在电能质量监测中的应用 4
三、智能电网电能质量问题诊断 5
（一）常见电能质量问题分类与特征 5
（二）基于人工智能的故障诊断方法 5
（三）谐波污染源定位技术研究 6
四、智能电网电能质量改善策略 7
（一）主动配电网中的电能质量控制 7
（二）分布式电源接入对电能质量的影响及对策 7
（三）储能系统在电能质量改善中的应用 8
结 论 9
本文聚焦于智能电网中的电能质量监测与改善方法，旨在提升电力系统的稳定性和可靠性。文章首先阐述了智能电网电能质量监测的研究背景及电能质量改善方法的研究意义，并分析了国内外在该领域的研究现状。在电能质量监测技术方面，文章详细介绍了电能质量参数的实时监测方法，探讨了分布式监测系统的架构设计，并分析了大数据在电能质量监测中的创新应用，为电能质量的全面监测提供了技术支持。针对电能质量问题诊断，文章分类总结了常见的电能质量问题及其特征，提出了基于人工智能的故障诊断方法，并研究了谐波污染源定位技术，为电能质量问题的精准识别提供了有效手段。在电能质量改善策略方面，文章探讨了主动配电网中的电能质量控制方法，分析了分布式电源接入对电能质量的影响及应对策略，并研究了储能系统在电能质量改善中的实际应用，为电能质量的综合改善提供了全面指导。本研究不仅丰富了智能电网电能质量监测与改善的理论体系，也为电力系统的优化运行和可持续发展提供了重要参考。
关键词：智能电网；电能质量监测；深度学习；长短期记忆网络；多目标优化
Abstract
This article focuses on the monitoring and improvement methods of power quality in smart grids, aiming to enhance the stability and reliability of the power system. The article first elaborates on the research background of smart grid power quality monitoring and the significance of improving power quality methods, and analyzes the current research status in this field at home and abroad. In terms of power quality monitoring technology, the article provides a detailed introduction to real-time monitoring methods for power quality parameters, explores the architecture design of distributed monitoring systems, and analyzes the innovative application of big data in power quality monitoring, providing technical support for comprehensive monitoring of power quality. Regarding the diagnosis of power quality issues, this article categorizes and summarizes common power quality problems and their characteristics, proposes an artificial intelligence based fault diagnosis method, and studies harmonic pollution source localization technology, providing an effective means for accurate identification of power quality issues. In terms of power quality improvement strategies, this article explores the power quality control methods in active distribution networks, analyzes the impact of distributed power source access on power quality and response strategies, and studies the practical application of energy storage systems in power quality improvement, providing comprehensive guidance for the comprehensive improvement of power quality. This study not only enriches the theoretical system of smart grid power quality monitoring and improvement, but also provides important references for the optimized operation and sustainable development of the power system.
Keywords：Smart Grid; Power Quality Monitoring; Deep Learning; Long Short-Term Memory Network; Multi-ob jective Optimization
目 录
摘要 I
Abstract II
一、绪论 1
（一）智能电网电能质量监测的研究背景 1
（二）电能质量改善方法的研究意义 1
（三）国内外研究现状分析 2
二、智能电网电能质量监测技术 3
（一）电能质量参数实时监测方法 3
（二）分布式监测系统架构设计 3
（三）大数据在电能质量监测中的应用 4
三、智能电网电能质量问题诊断 5
（一）常见电能质量问题分类与特征 5
（二）基于人工智能的故障诊断方法 5
（三）谐波污染源定位技术研究 6
四、智能电网电能质量改善策略 7
（一）主动配电网中的电能质量控制 7
（二）分布式电源接入对电能质量的影响及对策 7
（三）储能系统在电能质量改善中的应用 8
结 论 9
参考文献 10
